An accelerated field simulator for aboveground testing of wood preservatives
Bibliographic record
Abstract
The wood preservation industry in Canada is interested in new preservatives, some of which are intended only for aboveground uses. Canada's Pest Management Regulatory Agency requires data from field tests under Canadian conditions but these can take many years to generate results. FPInnovations has, therefore, developed an accelerated field simulation test for aboveground applications. This paper provides examples of results on four formulations tested for one anonymous client. Short lengths of treated and untreated nominal 2 by 6s were supported on stainless steel screws and intermittently sprayed with deionized water from above. All of the test material was exposed to spores of Gloeophyllum sepiarium and Oligoporus placentus from fruiting bodies grown on Petri dishes that were suspended from the ceiling and to spores from outside air introduced at intervals via a fan. In addition, half of the boards were exposed to mycelial colonization from wood blocks infected with G. sepiarium. The test material was evaluated using the AWPA rating system. PCR and DNA sequencing demonstrated that infection had in many cases occurred via spore germination. Two years of data suggest, at least on spruce, this new test method is capable of discriminating between treatments that may be resistant only to spore germination and those that are resistant to both spores and mycelium.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".